Imperfections Lower the Simulation Cost of Quantum Computers
+ With a few quantum bits, an ideal quantum computer can process vast amounts of information in a coordinated way, making it significantly more powerful than a classical counterpart. This predicted power increase will be great for users but is bad for physicists trying to simulate on a classical computer how an ideal quantum computer will behave.
+ Now, a trio of researchers has shown that they can substantially reduce the resources needed to do these simulations if the quantum computer is “imperfect”.
Today’s state-of-the-art quantum computers—including Sycamore—are NISQ devices. The algorithms the team used are based on so-called tensor network methods, specifically matrix product states (MPS), which are good for simulating noise and so are naturally suited for studying NISQ devices. MPS methods approximate low-entangled quantum states with simpler structures, so they provide a data-compression-like protocol that can make it less computationally expensive to classically simulate imperfect quantum computers.
+ In 2019, Google claimed to have achieved the quantum computing milestone known as “quantum advantage,” publishing results showing that their quantum computer Sycamore had performed a calculation that was essentially impossible for a classical one.
+ More specifically, Google claimed that they had completed a three-minute quantum computation—which involved generating random numbers with Sycamore’s 53 qubits—that would take thousands of years on a state-of-the-art classical supercomputer, such as IBM’s Summit.
+ IBM quickly countered the claim, arguing that more efficient memory storage would reduce the task time on a classical computer to a couple of days. The claims and counterclaims sparked an industry clash and an intense debate among supporters in the two camps.
Source: Physics. Jordi Tura, Imperfections Lower the Simulation Cost of Quantum Computers…
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